José Antonio Hernández López

According to our database, José Antonio Hernández López authored at least 28 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

ModelXGlue: a benchmarking framework for ML tools in MDE.

José Antonio Hernández López, Jesús Sánchez Cuadrado, Riccardo Rubei, Davide Di Ruscio

Softw. Syst. Model., August, 2025

Why Do Machine Learning Notebooks Crash? An Empirical Study on Public Python Jupyter Notebooks.

Yiran Wang, Willem Meijer, José Antonio Hernández López, Ulf Nilsson, Dániel Varró

IEEE Trans. Software Eng., July, 2025

SENAI: Towards Software Engineering Native Generative Artificial Intelligence.

Mootez Saad, José Antonio Hernández López, Boqi Chen, Neil A. Ernst, Dániel Varró, Tushar Sharma

CoRR, March, 2025

Dataset of paper "Why do Machine Learning Notebooks Crash?".

Yiran Wang, Willem Meijer, José Antonio Hernández López, Ulf Nilsson, Dániel Varró

Dataset, March, 2025

On Inter-Dataset Code Duplication and Data Leakage in Large Language Models.

José Antonio Hernández López, Boqi Chen, Mootez Saad, Tushar Sharma, Dániel Varró

IEEE Trans. Software Eng., January, 2025

An Adaptive Language-Agnostic Pruning Method for Greener Language Models for Code.

Mootez Saad, José Antonio Hernández López, Boqi Chen, Dániel Varró, Tushar Sharma

Proc. ACM Softw. Eng., 2025

The Power of Types: Exploring the Impact of Type Checking on Neural Bug Detection in Dynamically Typed Languages.

Boqi Chen, José Antonio Hernández López, Gunter Mussbacher, Dániel Varró

Proceedings of the 47th IEEE/ACM International Conference on Software Engineering, 2025

2024

Dataset of paper "Why do Machine Learning Notebooks Crash?".

Yiran Wang, Willem Meijer, José Antonio Hernández López, Ulf Nilsson, Dániel Varró

Dataset, November, 2024

ModelSet: A labelled dataset of software models for machine learning.

José Antonio Hernández López, Javier Luis Cánovas Izquierdo, Jesús Sánchez Cuadrado

Sci. Comput. Program., January, 2024

Why do Machine Learning Notebooks Crash?

Yiran Wang, Willem Meijer, José Antonio Hernández López, Ulf Nilsson, Dániel Varró

CoRR, 2024

ALPINE: An adaptive language-agnostic pruning method for language models for code.

Mootez Saad, José Antonio Hernández López, Boqi Chen, Dániel Varró, Tushar Sharma

CoRR, 2024

On Inter-dataset Code Duplication and Data Leakage in Large Language Models.

José Antonio Hernández López, Boqi Chen, Tushar Sharma, Dániel Varró

CoRR, 2024

Artifacts for "Text2VQL: Teaching a Model Query Language to Open-Source Language Models with ChatGPT".

José Antonio Hernández López, Máté Földiák, Dániel Varró

Dataset, 2024

Artifacts for "Text2VQL: Teaching a Model Query Language to Open-Source Language Models with ChatGPT".

José Antonio Hernández López, Máté Földiák, Dániel Varró

Dataset, 2024

Using Run-Time Information to Enhance Static Analysis of Machine Learning Code in Notebooks.

Yiran Wang, José Antonio Hernández López, Ulf Nilsson, Dániel Varró

Proceedings of the Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024

Text2VQL: Teaching a Model Query Language to Open-Source Language Models with ChatGPT.

José Antonio Hernández López, Máté Földiák, Dániel Varró

Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, 2024

ModelMate: A recommender for textual modeling languages based on pre-trained language models.

Carlos Durá, José Antonio Hernández López, Jesús Sánchez Cuadrado

Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, 2024

2023

On Inter-dataset Code Duplication and Data Leakage in Large Language Models.

José Antonio Hernández López, Boqi Chen, Mootez Saad, Tushar Sharma, Dániel Varró

Dataset, December, 2023

Generating Structurally Realistic Models With Deep Autoregressive Networks.

José Antonio Hernández López, Jesús Sánchez Cuadrado

IEEE Trans. Software Eng., April, 2023

Word Embeddings for Model-Driven Engineering.

José Antonio Hernández López, Carlos Durá, Jesús Sánchez Cuadrado

Proceedings of the 26th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, 2023

Automated Domain Modeling with Large Language Models: A Comparative Study.

Kua Chen, Yujing Yang, Boqi Chen, José Antonio Hernández López, Gunter Mussbacher, Dániel Varró

Proceedings of the 26th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, 2023

2022

ModelSet: a dataset for machine learning in model-driven engineering.

José Antonio Hernández López, Javier Luis Cánovas Izquierdo, Jesús Sánchez Cuadrado

Softw. Syst. Model., 2022

An efficient and scalable search engine for models.

José Antonio Hernández López, Jesús Sánchez Cuadrado

Softw. Syst. Model., 2022

Machine learning methods for model classification: a comparative study.

José Antonio Hernández López, Riccardo Rubei, Jesús Sánchez Cuadrado, Davide Di Ruscio

Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems, 2022

Using the ModelSet dataset to support machine learning in model-driven engineering.

José Antonio Hernández López, Javier Luis Cánovas Izquierdo, Jesús Sánchez Cuadrado

Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, 2022

AST-Probe: Recovering abstract syntax trees from hidden representations of pre-trained language models.

José Antonio Hernández López, Martin Weyssow, Jesús Sánchez Cuadrado, Houari A. Sahraoui

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, 2022

2021

Towards the Characterization of Realistic Model Generators using Graph Neural Networks.

José Antonio Hernández López, Jesús Sánchez Cuadrado

Proceedings of the 24th International Conference on Model Driven Engineering Languages and Systems, 2021

2020

MAR: a structure-based search engine for models.

José Antonio Hernández López, Jesús Sánchez Cuadrado

Proceedings of the MoDELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems, 2020